{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgUAAAFkCAYAAACw3EhvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x13bf2cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 随机生成1000个点，围绕在y=0.1x+0.3的直线周围\n",
    "num_points = 1000\n",
    "vectors_set = []\n",
    "for i in range(num_points):\n",
    "    x1 = np.random.normal(0.0, 0.55)\n",
    "    y1 = x1 * 0.1 + 0.3 + np.random.normal(0.0, 0.03)\n",
    "    vectors_set.append([x1, y1])\n",
    "\n",
    "# 生成一些样本\n",
    "x_data = [v[0] for v in vectors_set]\n",
    "y_data = [v[1] for v in vectors_set]\n",
    "\n",
    "plt.scatter(x_data,y_data,c='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "W = [0.45255446] b = [0.] loss = 0.1333605\n",
      "W = [0.3362347] b = [0.30536044] loss = 0.018502109\n",
      "W = [0.26173285] b = [0.30345154] loss = 0.009149097\n",
      "W = [0.21077418] b = [0.30222896] loss = 0.0047736885\n",
      "W = [0.17592025] b = [0.30139273] loss = 0.002726835\n",
      "W = [0.15208139] b = [0.30082077] loss = 0.0017693022\n",
      "W = [0.13577645] b = [0.30042958] loss = 0.0013213602\n",
      "W = [0.12462443] b = [0.300162] loss = 0.0011118094\n",
      "W = [0.11699685] b = [0.299979] loss = 0.00101378\n",
      "W = [0.11177985] b = [0.29985383] loss = 0.00096792064\n",
      "W = [0.1082116] b = [0.2997682] loss = 0.0009464675\n",
      "W = [0.10577104] b = [0.29970965] loss = 0.00093643134\n",
      "W = [0.10410178] b = [0.29966962] loss = 0.0009317366\n",
      "W = [0.10296007] b = [0.2996422] loss = 0.0009295403\n",
      "W = [0.10217918] b = [0.2996235] loss = 0.00092851295\n",
      "W = [0.10164507] b = [0.29961067] loss = 0.00092803227\n",
      "W = [0.10127977] b = [0.2996019] loss = 0.00092780706\n",
      "W = [0.10102991] b = [0.2995959] loss = 0.00092770194\n",
      "W = [0.10085902] b = [0.2995918] loss = 0.00092765293\n",
      "W = [0.10074213] b = [0.299589] loss = 0.0009276299\n",
      "W = [0.10066219] b = [0.29958707] loss = 0.0009276191\n"
     ]
    }
   ],
   "source": [
    "# 生成1维的W矩阵，取值是[-1,1]之间的随机数\n",
    "with tf.name_scope('weight'):\n",
    "    W = tf.Variable(tf.random_uniform([1], -1.0, 1.0), name='W')\n",
    "# 生成1维的b矩阵，初始值是0\n",
    "with tf.name_scope('bias'):\n",
    "    b = tf.Variable(tf.zeros([1]), name='b')\n",
    "# 经过计算得出预估值y\n",
    "with tf.name_scope('y'):\n",
    "    y = W * x_data + b\n",
    "\n",
    "# 以预估值y和实际值y_data之间的均方误差作为损失\n",
    "with tf.name_scope('loss'):\n",
    "    loss = tf.reduce_mean(tf.square(y - y_data), name='loss')\n",
    "# 采用梯度下降法来优化参数\n",
    "optimizer = tf.train.GradientDescentOptimizer(0.5)\n",
    "# 训练的过程就是最小化这个误差值\n",
    "train = optimizer.minimize(loss, name='train')\n",
    "\n",
    "sess = tf.Session()\n",
    "\n",
    "init = tf.global_variables_initializer()\n",
    "sess.run(init)\n",
    "\n",
    "# 初始化的W和b是多少\n",
    "print (\"W =\", sess.run(W), \"b =\", sess.run(b), \"loss =\", sess.run(loss))\n",
    "# 执行20次训练\n",
    "for step in range(20):\n",
    "    sess.run(train)\n",
    "    # 输出训练好的W和b\n",
    "    print (\"W =\", sess.run(W), \"b =\", sess.run(b), \"loss =\", sess.run(loss))\n",
    "# writer = tf.train.SummaryWriter(\"logs/\", sess.graph)\n",
    "writer = tf.summary.FileWriter(\"logs/\", sess.graph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgUAAAFkCAYAAACw3EhvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x16648780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x_data,y_data,c='r')\n",
    "plt.plot(x_data,sess.run(W)*x_data+sess.run(b))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
